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Background: Tumor development is critically dependent on the supporting stroma consisting of inflammatory cells and fibroblasts. This study intended to improve prognostic prediction for early colorectal cancer (CRC) by combined estimation of T-lymphocyte and stroma fractions with conventional markers., Methods: In total 509 and 1041 stage II/ΙΙΙ CRC from the VICTOR and QUASAR 2 trials were included as a training set and a validation set, respectively. Intratumoral CD8 + T-lymphocytes and stroma were identified and quantified by machine-based learning on digital sections. The primary endpoint was to evaluate the prognostic value of the combined marker for time to recurrence (TTR)., Findings: For low-risk patients (n = 598; stage Ⅱ, and stage ΙΙΙ pT1-3 pN1 with neither lymphatic (L - ) nor vascular (V - ) invasion), low stroma fraction (n = 511) identified a good prognostic subgroup with 5-year TTR of 86% (95% CI 83-89), versus the high stroma subgroup TTR of 78% (HR = 1.75, 95% CI 1.05-2.92; P = 0.029). For high-risk patients (n = 394; stage ΙΙΙ pT3 pN1 L + /V + , pT4, or pN2), combined low CD8 + and high stroma fraction identified a poor prognostic subgroup (n = 34) with 5-year TTR of 29% (95% CI 17-50), versus the high CD8 + fraction and low stroma fraction subgroup (n = 138) of 64% (HR = 2.86, 95% CI 1.75-4.69; P < 0.001)., Interpretation: Quantification of intratumoral CD8 + T-lymphocyte and stroma fractions can be combined with conventional prognostic markers to improve patient stratification., Competing Interests: Declaration of Competing Interest DK reports personal fees from Oxford Cancer Biomarkers (Oxford, UK), outside the submitted work. All other authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

The combination of DNA ploidy and automatically estimated stroma fraction has been shown to correlate with recurrence and cancer death in colorectal cancer. We aimed to extend this observation and evaluate the prognostic importance of this combined marker in prostate cancer. DNA ploidy status was determined by image cytometry and the stroma fraction was estimated automatically on hematoxylin and eosin stained sections in three tumor samples from each patient to account for tumor heterogeneity. The optimal threshold for low (≤56%) and high (>56%) stroma fraction was identified in a discovery cohort (n = 253). The combined marker was validated in an independent patient cohort (n = 259) with biochemical recurrence as endpoint. The combined marker predicted biochemical recurrence independently in the validation cohort. Multivariable analysis showed that the highest risk of recurrence was observed for patients with samples that had both non-diploid ploidy status and a high stroma fraction (hazard ratio: 2.51, 95% confidence interval: 1.18-5.34). In conclusion, we suggest the combination of DNA ploidy and automatically estimated stroma fraction as a prognostic marker for the risk stratification of prostate cancer patients. It may also be a potential generic marker as concurrent results have been described in colorectal cancer., (© 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: When diagnosing cancer, it is often difficult to predict the further growth and spread of the tumour. One of the features of cancer is an abnormality in the amount of DNA in cancer cell nuclei, so-called DNA aneuploidy. Extensive abnormalities are often due to an unstable genome, which leads to an accumulation of mutations, dysregulation of genes and loss of cell cycle control. This article aims to provide an overview of the prognostic value of DNA ploidy analyses in ovarian, endometrial, prostate and colorectal carcinoma., Material and Method: This review article is based on literature searches in PubMed for the period 2000–2016., Results: The search resulted in 308 articles. Thirty-three of these, representing an analysis of more than 18 000 tumours, fulfilled the inclusion criteria. In 30 of the 33 articles, a significant correlation was found between DNA ploidy and disease outcome for patients with ovarian, endometrial, prostate and colorectal carcinoma. Patients with aneuploid tumours had a poorer prognosis than those with diploid tumours., Interpretation: DNA ploidy analysis is a prognostic method for patients with ovarian and endometrial carcinoma, and is used as a guide to options for supplemental treatment and fertility-sparing surgery. A review of publications in recent years of DNA ploidy analyses for prostate and colorectal carcinoma reveals that these patient groups may also benefit from these measurements. In general terms, DNA ploidy analyses may help to increase knowledge of who needs supplemental treatment and who does not – which may be advantageous in avoiding overtreatment.

Background: Most endometrial carcinoma patients are diagnosed at an early stage with a good prognosis. However, a relatively low fraction with lethal disease constitutes a substantial number of patients due to the high incidence rate. Preoperative identification of patients with high risk and low risk for poor outcome is necessary to tailor treatment. Nucleotyping refers to characterization of cell nuclei by image cytometry, including the assessment of chromatin structure by nuclear texture analysis. This method is a strong prognostic marker in many cancers but has not been evaluated in preoperative curettage specimens from endometrial carcinoma., Methods: The prognostic impact of changes in chromatin structure quantified with Nucleotyping was evaluated in preoperative curettage specimens from 791 endometrial carcinoma patients prospectively included in the MoMaTEC multicenter trial., Results: Nucleotyping was an independent prognostic marker of disease-specific survival in preoperative curettage specimens among patients with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I-II disease (HR=2.9; 95% CI, 1.2-6.5; P = 0.013) and significantly associated with age, FIGO stage, histologic type, histologic grade, myometrial infiltration, lymph node status, curettage histology type, and DNA ploidy., Conclusions: Nucleotyping in preoperative curettage specimens is an independent prognostic marker for disease-specific survival, with potential to supplement existing parameters for risk stratification to tailor treatment., Impact: This is the first study to evaluate the prognostic impact of Nucleotyping in curettage specimens from endometrial carcinoma and shows that this may be a clinically useful prognostic marker in endometrial cancer. External validation is warranted. Cancer Epidemiol Biomarkers Prev; 26(1); 61-67. ©2016 AACR., (©2016 American Association for Cancer Research.)

Overtreatment is a major concern in men diagnosed with prostate cancer. The aim of this study was to evaluate the combined prognostic role of three frequent molecular alterations in prostate cancer, namely relative 8q gain, ERG overexpression, and loss of PTEN expression, in a series of 136 patients with prostate cancer treated with prostatectomy and with a long follow-up. Fluorescent in situ hybridization was used to detect the relative copy number of 8q and immunohistochemistry was used for quantitative assessment of ERG and PTEN expression. During a median follow-up period of 117.8 months, 66 (49%) patients had disease recurrence. Relative 8q gain, ERG overexpression, and loss of PTEN expression were observed in 18%, 56%, and 33% of the cases, respectively. No association with patient recurrence-free survival was found for relative 8q gain or ERG overexpression on their own, whereas loss of PTEN expression was associated with worse recurrence-free survival (P=.006). Interestingly, in the subgroup of patients with normal PTEN expression, we found that the combined relative 8q gain/ERG overexpression is associated with high risk of recurrence (P=.008), suggesting that alternative mechanisms exist for progression into clinically aggressive disease. Additionally, in intermediate-risk patients with normal PTEN expression in their tumors, the combination of 8q gain/ERG overexpression was associated with a poor recurrence-free survival (P<.001), thus indicating independent prognostic value. This study shows that the combined analysis of 8q, ERG and PTEN contributes to an improved clinical outcome stratification of prostate cancer patients treated with radical prostatectomy., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Aberrations in the Wnt/beta-catenin signalling pathway are suggested as mediators of chromosomal instability and carcinogenesis. beta-catenin acts both as a component of the membranous adhesion system, and as a transcription activator in the nucleus. beta-Catenin immunoreactivity was evaluated in 353 uterine sarcomas (US) including 231 leiomyosarcomas (LMS), 82 endometrial stromal sarcomas (ESS), 22 adenosarcomas (AS) and 18 undifferentiated uterine sarcomas (UUS). Up-regulated membranous beta-catenin was observed in 25% of the LMS (p=0.039), 21% of the ESS (p=0.072) and 39% of the UUS (p=0.025). Cytoplasmic beta-catenin was up-regulated in 36% of the LMS (p=0.008) and 33% of the UUS (p=0.028). Nuclear beta-catenin expression was observed in 23% of the LMS (p=0.051), 61% of ESS (p=0.628) and in the sarcoma component of 68% of the AS. In patients with LMS, membranous beta-catenin was associated with poor crude survival in univariate (p=0.045), but not in multivariate analyses. In patients with ESS, nuclear beta-catenin expression was related to spread of tumour (p=0.033), but not to survival. The observation of up-regulated beta-catenin expression in US might suggest a so far undocumented role for the Wnt/beta-catenin pathway in these malignancies.

The CTNNB1 gene and its product beta-catenin, a regulator of the Wnt signalling pathway, is often mutated and deregulated in human malignancies. Down stream targets of the Wnt signalling pathway are linked to genomic instability. In this study, the impact of beta-catenin expression on genomic instability in ovarian carcinoma, as determined by DNA ploidy, was investigated. Expression of beta-catenin was examined by immunohistochemistry in 253 ovarian carcinomas. The results were related to genomic instability and clinicopathological features of the patients. Membrane associated staining of beta-catenin was detected in nearly all cases with no correlation to clinical parameters. Most of the samples also had cytoplasmic (84%), while only 13% had nuclear beta-catenin localisation. A significant association between beta-catenin expression (cytoplasmic and nuclear) and histological subtype and degree of differentiation was observed. Nuclear beta-catenin was almost exclusively present in endometroid carcinomas. 53% of all endometroid tumours were positive for nuclear beta-catenin expression (P<0.0001). Mucinous carcinomas had the highest degree of cytoplasmic beta-catenin expression (92%), followed by endometroid (92%), mixed (90%), serous (82%), unclassified adenocarcinomas (81%), carcinomas clear cell and (70%), (P=0.01). Tumours with differentiation grade 1 (16%) and 2 (24%) had higher nuclear beta-catenin expression than grade 3 and clear cell carcinomas (6%) (P=0.012). Better prognostic outcome was found for patients with nuclear beta-catenin localisation as compared to the cases without (P=0.027). In conclusion, the study showed no correlation between beta-catenin expression in ovarian carcinoma and FIGO stage and genomic instability as determined by DNA ploidy status. However, nuclear beta-catenin expression was strongly associated with endometroid histological subtype. Finally, in ovarian cancer, although beta-catenin staining seems to be of prognostic importance with respect to nuclear staining in univariate analysis, only DNA ploidy status, histological grade and FIGO staging were of independent prognostic significance in multivariate analysis.

In many popular texture analysis methods, second or higher order statistics on the relation between pixel gray level values are stored in matrices. A high dimensional vector of predefined, nonadaptive features is then extracted from these matrices. Identifying a few consistently valuable features is important, as it improves classification reliability and enhances our understanding of the phenomena that we are modeling. Whatever sophisticated selection algorithm we use, there is a risk of selecting purely coincidental "good" feature sets, especially if we have a large number of features to choose from and the available data set is limited. In a unified approach to statistical texture feature extraction, we have used class distance and class difference matrices to obtain low dimensional adaptive feature vectors for texture classification. We have applied this approach to four relevant texture analysis methods. The new adaptive features outperformed the classical features when applied to the most difficult set of 45 Brodatz texture pairs. Class distance and difference matrices also clearly illustrated the difference in texture between cell nucleus images from two different prognostic classes of early ovarian cancer. For each of the texture analysis methods, one adaptive feature contained most of the discriminatory power of the method.